Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Neural Circuits

Neural Circuits

Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...

Electrical Synapses

Electrical Synapses

Electrical synapses found in all nervous systems play important and unique roles. In these synapses, the presynaptic and postsynaptic membranes are very close together (3.5 nm) and are actually physically connected by channel proteins forming gap junctions.
Gap junctions allow the current to pass directly from one cell to the next. In contrast, in the chemical synapse, the neurotransmitters carry the information through the synaptic cleft from one neuron to the next. They consist of two...

The Role of Ion Channels in Neuronal Computation

The Role of Ion Channels in Neuronal Computation

A postsynaptic neuron usually receives numerous impulses from several other presynaptic neurons. The axon hillock of the postsynaptic neuron integrates all these signals and determines the likelihood of firing an action potential.
Sometimes a single EPSP is strong enough to induce an action potential in the postsynaptic neuron. However, multiple presynaptic inputs must often create EPSPs around the same time for the postsynaptic neuron to be sufficiently depolarized to fire an action potential.

Voltage-gated Ion Channels

Voltage-gated Ion Channels

Voltage-gated ion channels are transmembrane proteins that open and close in response to changes in the membrane potential. They are present on the membranes of all electrically excitable cells such as neurons, heart, and muscle cells.
Generally, all voltage-gated ion channels have a 'voltage-sensing domain' that spans the lipid bilayer. The charged residues in the sensor move in response to the membrane potential changes that open the channel allowing ions movement. There are several types of...

Voltage-gated Ion Channels

Voltage-gated Ion Channels

Voltage-gated ion channels are transmembrane proteins that open and close in response to changes in the membrane potential. They are present on the membranes of all electrically excitable cells such as neurons, heart, and muscle cells.
Generally, all voltage-gated ion channels have a 'voltage-sensing domain' that spans the lipid bilayer. The charged residues in the sensor move in response to the membrane potential changes that open the channel allowing ions movement. There are several types of...

Integration of Synaptic Events

Integration of Synaptic Events

Synaptic integration mainly includes the summation of graded potentials. Graded potentials, regardless of their type, cause subtle alterations in membrane voltage, resulting in either depolarization or hyperpolarization. These incremental changes, when combined or summed, can propel the neuron toward its threshold. Consider, for example, a membrane experiencing a +15 mV shift, causing it to depolarize from -70 mV to -55 mV. In this scenario, graded potentials govern the membrane's ability to...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Identification of drug candidates for rescue of SOX17 gene targets in pulmonary arterial hypertension.

bioRxiv : the preprint server for biology·2026

Same author

Does Support Meet the Need? A Focus Group Study on Parental Support and Students' Psychological Need Satisfaction in a Minority School Context.

Healthcare (Basel, Switzerland)·2026

Same author

Metrics for spin-based computing.

Nature reviews. Physics·2026

Same author

Flexible integration of natural stimuli by auditory cortical neurons.

Journal of neurophysiology·2026

Same author

Representational similarity modulates neural and behavioral signatures of novelty.

Neuron·2026

Same author

Functional reorganization of motor cortex connectivity during learning.

bioRxiv : the preprint server for biology·2026

Search research articles

Related Experiment Video

Updated: Jun 16, 2026

Modeling Biological Membranes with Circuit Boards and Measuring Electrical Signals in Axons: Student Laboratory Exercises

Modeling Biological Membranes with Circuit Boards and Measuring Electrical Signals in Axons: Student Laboratory Exercises

Published on: January 18, 2011

Connectivity reflects coding: a model of voltage-based STDP with homeostasis.

Claudia Clopath¹, Lars Büsing, Eleni Vasilaki

¹Laboratory of Computational Neuroscience, Brain-Mind Institute and School of Computer and Communication Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland. claudia.clopath@epfl.ch

Nature Neuroscience

|January 26, 2010

Summary

This study models spike timing-dependent plasticity (STDP) to explain brain connectivity. The model shows how different neural coding principles lead to varied synaptic connection patterns, suggesting fast plasticity.

More Related Videos

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Published on: June 21, 2022

Dynamic Clamp Methods to Investigate Impaired Neuronal Excitability Associated with Autism

Dynamic Clamp Methods to Investigate Impaired Neuronal Excitability Associated with Autism

Published on: October 17, 2025

Related Experiment Videos

Last Updated: Jun 16, 2026

Modeling Biological Membranes with Circuit Boards and Measuring Electrical Signals in Axons: Student Laboratory Exercises

Modeling Biological Membranes with Circuit Boards and Measuring Electrical Signals in Axons: Student Laboratory Exercises

Published on: January 18, 2011

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Published on: June 21, 2022

Dynamic Clamp Methods to Investigate Impaired Neuronal Excitability Associated with Autism

Dynamic Clamp Methods to Investigate Impaired Neuronal Excitability Associated with Autism

Published on: October 17, 2025

Area of Science:

Computational neuroscience
Neural plasticity

Background:

Cortical connectivity features a few strong, sometimes bidirectional, connections amidst many weak ones.
Existing models struggle to fully explain these observed electrophysiological connectivity patterns.

Purpose of the Study:

To develop a novel model of spike timing-dependent plasticity (STDP) that explains cortical connectivity patterns.
To investigate how different neural coding principles influence synaptic plasticity and network structure.

Main Methods:

Developed an STDP model incorporating presynaptic spike arrival and postsynaptic membrane potential, filtered by two time constants.
Simulated a recurrent network of spiking neurons using the developed plasticity rule.
Analyzed connectivity patterns under different input correlation types (spatio-temporal vs. spatial) and coding schemes (temporal vs. rate).

Main Results:

The STDP model reproduced nonlinear effects and voltage dependence observed in experiments.
Simulations resulted in localized receptive fields and connectivity patterns reflecting the neural code.
Strong connections were predominantly unidirectional under temporal coding with spatio-temporal correlations, but bidirectional under rate coding with spatial correlations.

Conclusions:

Variable cortical connectivity patterns may arise from different neural coding principles across brain areas.
The developed plasticity rule offers a potential mechanism for generating observed brain network structures.
Simulations suggest that synaptic plasticity in neural networks is a rapid process.